Accelerate AI Development with Data Center Servers and Workstations
Featuring Nvidia's latest GPU Architecture
Designed for a new type of emerging data center that process and refine mountains of data to produce intelligence. Ideal for workloads such as AI training and inference. Supported by Nvidia's softare foundation used in AI, with Nvidia's CUDA libraries and over 4000 third-party and open-source software. Accelerate data science pipeline, streamline developement, and deploy production grade AI applications.
Preconfigured with the Latest Frameworks to Help Build a Base for an AI Infrastructure
Docker
Docker's technology is unique because it focuses on the requirements of developers and systems operators to separate application dependencies from infrastructure. A container is a standard unit of software that packages up code and all its dependencies, so the application runs quickly and reliably from one computing environment to another. A Docker container image is a lightweight, standalone, executable package of software that includes everything needed to run an application: code, runtime, system tools, system libraries and settings. Containerization provides a portable and efficient solution for development and deployment.
CUDA
The NVIDIA CUDA Toolkit provides a development environment for creating high performance GPU-accelerated applications. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The toolkit includes GPUaccelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to deploy your application
cuDNN
The NVIDIA CUDA Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers.
Anaconda
Conda is an open source package management system and environment management system that runs on Windows, macOS and Linux. Conda quickly installs, runs and updates packages and their dependencies. Conda easily creates, saves, loads and switches between environments on your local computer. It was created for Python programs, but it can package and distribute software for any language.
Finding the Perfect GPU Server Solution to Meet Required AI Tasks
Performance
Whether just starting your AI journey with one GPU or adding to your data center with servers up to ten GPUs or adding GPU clusters for unbelievable computational power, we can help find the absolutely best solution.
Power
Energy efficient servers plays a huge factor in maintaining lower costs and keeping energy consumption to a minimum.
Budget
Finding the right system to match your budget. Puzzling together servers that meet your minimum specifications at a still cost effective price to really get the value from your budget.
Scaling
With the idea that these servers are not just for today, but meant to scale and expand beyond today's needs. If a new technology or new features develop, these servers can provide room for upgrades or expansion with more accelerated compute power.
Need Help Configuring a Solution?
Feel free to contact us and we'll help customize a solution according to your budget and requirement.
